import plotly.offline as pyo
from plotly.graph_objs import *
import chart_studio.plotly as py
import pandas as pd
from pandas import DataFrame
pyo.offline.init_notebook_mode()
stocks = py.get_figure("https://plotly.com/~rmuir/162/stock-closing-prices-for-apple-in-2012/")
stocks
other_stocks = py.get_figure('rmuir', 162)
other_stocks
pyo.iplot(stocks)
stocks['layout']['yaxis'].update({'range' : [0, 1000]})
pyo.iplot(stocks)
maximum = max(stocks['data'][0]['y'])
maximum
702.100021
stocks['layout']['yaxis'].update({'range' : [0, maximum * 1.05]})
pyo.iplot(stocks)
df = pd.read_csv(r"../Data/BoEBaseRate.csv")
df.head(5)
| Unnamed: 0 | VALUE | DATE | |
|---|---|---|---|
| 0 | 0 | 11.5 | 1975-01-02 |
| 1 | 1 | 11.5 | 1975-01-03 |
| 2 | 2 | 11.5 | 1975-01-06 |
| 3 | 3 | 11.5 | 1975-01-07 |
| 4 | 4 | 11.5 | 1975-01-08 |
df.max()
Unnamed: 0 10485 VALUE 17.0 DATE 2016-06-23 dtype: object
df['strDate'] = pd.to_datetime(df['DATE'], format="%Y/%m/%d")
df.head()
| Unnamed: 0 | VALUE | DATE | strDate | |
|---|---|---|---|---|
| 0 | 0 | 11.5 | 1975-01-02 | 1975-01-02 |
| 1 | 1 | 11.5 | 1975-01-03 | 1975-01-03 |
| 2 | 2 | 11.5 | 1975-01-06 | 1975-01-06 |
| 3 | 3 | 11.5 | 1975-01-07 | 1975-01-07 |
| 4 | 4 | 11.5 | 1975-01-08 | 1975-01-08 |
df.max()
Unnamed: 0 10485 VALUE 17.0 DATE 2016-06-23 strDate 2016-06-23 00:00:00 dtype: object
df['VALUE'].max()
17.0
df.min()
Unnamed: 0 0 VALUE 0.5 DATE 1975-01-02 strDate 1975-01-02 00:00:00 dtype: object
df['VALUE'].min()
0.5